Multi-attribute Analysis Research Articles

2D-CEX-FcRn-MS to Study Structure/Function Relation of mAb Charge Variants.

The automated elucidation of the interplay between monoclonal antibody (mAb) structure and function using two-dimensional liquid chromatography-mass spectrometry (2D-LC-MS) is reported. Charge variants, induced through forced degradation, are resolved by first-dimension (1D) cation-exchange chromatography (CEX) and subsequently collected in loops installed on a multiple heart-cutting valve prior to transfer to second-dimension (2D) neonatal crystallizable fragment receptor (FcRn) affinity chromatography coupled with MS. As such, binding affinity of the latter mAb variants can elegantly be assessed and a first glimpse of identity provided. To maximize MS sensitivity, charge variants are unfolded upon eluting from the 2D affinity column by postcolumn addition of a denaturing solution. Further structural details, i.e., modification sites and chain distribution, are unraveled by a multidimensional LC-MS (mD-LC-MS) setup incorporating 1D CEX and parallel online middle-up and bottom-up LC-MS analysis in the subsequent dimensions. Identified charge variants could be ranked according to their affinity for FcRn. Binding is predominantly impacted by heavy chain (HC) M253 oxidation and to a lesser extend, M429 oxidation. Oxidation of both HCs more drastically affects FcRn interaction compared to single-chain oxidation, and the more oxidation, the less binding. Other modifications, such as HC glycosylation, HC N385/390, and N326 deamidation or HC C-terminal processing, are not shown to affect binding. The streamlined platform is challenged against the established workflow involving offline collection of charge variants and structural and functional assessment by, respectively, LC-MS and enzyme-linked immunosorbent assay (ELISA). A decent correlation is demonstrated between the binding affinity measured with ELISA and 2D FcRn affinity chromatography. In addition, throughput is improved (7-fold), material requirements are substantially reduced (2 orders of magnitude), and sample preparation artifacts and loss are minimized. With the simultaneous determination of mAb structure and function, the current study takes the concept of multiattribute analysis to the next level, thereby contributing to the future development of safer and more effective antibody therapeutics.

CE-MS and CE-MS/MS for the multiattribute analysis of monoclonal antibody variants at the subunit level

The analysis of product-related substances and impurities is a critical step in the biopharmaceutical quality control of multiattribute monoclonal antibodies (mAbs), as posttranslational modifications or other variants can influence the product's biological activity. Many approaches are available for variant analysis; however, they are either variant-specific, mAb-specific, time-consuming, or require expensive equipment. Here, we present a generic capillary electrophoretic method based on a neutral-coated capillary which was coupled to mass spectrometry (MS) via the nanoCEasy interface for mAb variant analysis at the subunit level (enzymatically digested and reduced mAb). The method enabled the separation of several (i) size variants (e.g. glycosylation variants) and (ii) charge variants (e.g. c-terminal lysin clipping) as well as (iii) multiple other proteoforms (e.g. additional glycation) and (iv) incompletely reduced subunits. Separated variants were confirmed by MS/MS fragmentation even for small mass deviations like deamidation or open disulfide bridges. The system, initially developed for one mAb, was tested with nine other IgG1s to show the general applicability of the system. The presented multiattribute method enables fast and detailed characterization of mAb variants with little sample preparation and relatively simple separation equipment enabling the separation of a large set of mAb variants.

Estimation of reservoir properties using pre-stack seismic inversion and neural network in mature oil field, Upper Assam basin, India

The mature oil fields require comprehensive characterization for enhanced hydrocarbon production, and subsequently demands estimation of reservoir properties. The key properties viz. volume of clay, effective-porosity, hydrocarbon-saturation has been evaluated for an aging Oligocene reservoir of Upper Assam basin, located in northeastern India from seismic and well log data. Elastic properties (acoustic and shear impedance) and density are derived from pre-stack inversion of 3D seismic data. These elastic properties are analyzed for their sensitivity for discrimination of lithology and fluid-content, and many derived attributes are computed from elastic properties. These attributes are assessed for their predictability to predict the target reservoir properties using multi-attribute analysis. For each of the target property neural network is trained with the most predictable attributes, and multi-dimensional, non-linear neural network models are created using multilayered feed forward neural network (MLFN), followed by Probabilistic neural network (PNN). The specific neural network models for each target property are employed for quantitative estimate of volume of clay, effective-porosity, hydrocarbon-saturation in inter-well regions. The estimated properties leverage the identification of untapped oil reserves and provide promising opportunity for enhanced production through drilling of infill wells.

The Influence Of Attitude On Farmers' Decision-Making Process In Using Certified Quality Seeds In Hilly Areas

The use of certified quality seeds is critical to increasing agricultural productivity. However, its use still needs to be improved in Bengkayang Regency, especially in hilly areas that pose unique challenges to agricultural practices. This study analyzed the influence of farmers' attitudes on their decision to use certified quality seed in the region. The research method used a mixed approach, combining descriptive analysis to collect data through a comprehensive questionnaire from farmers who have and have not used certified quality seeds. The sample consisted of 111 farmers in the Bengkayang district, representing a wide range of farming backgrounds and experiences. Fishbein's multi-attribute analysis and structural equation modeling (SEM) were used for in-depth data analysis, which provided vital insights into the factors influencing farmers' decisions. The results showed that farmers positively evaluated several attributes of certified quality seed, indicating confidence in its reliability, yield potential, and relevance to local conditions. These positive attitudes are mainly driven by agricultural motivation, perceived economic benefits, and careful decision evaluation. It is important to note that effective, cognitive, and cognitive attitudes jointly influence farmers' decision-making in selecting certified quality seed, indicating the complexity of the adoption process involving emotional, rational, and behavioral aspects. The results of this study provide valuable information for rice farmers and policymakers at the government level to design effective strategies to increase the use of quality seeds. Recommendations are developing targeted extension programs, improving access to quality seeds, and implementing incentives to encourage wider adoption among farmers in Bengkayang Regency.

Analisis Preferensi Konsumen Daging Ayam Broiler di Pasar Tradisional Kabupaten Jember Jawa Timur

Broiler chicken meat or usually known as broiler chicken, is easy to find in traditional markets and modern markets in Jember Regency. Consumers see a product as a collection of attributes that will determine a preference. A person's preferences can be formed through a person's behavior patterns which are based on several reasons, namely, previous experience and hereditary beliefs. The existence of people who still choose traditional markets amidst the rise of modern markets has become a social phenomenon. The aim of the research is to find out what attributes of broiler chicken meat are consumer preferences and what attributes are most considered by consumers. The research method used is descriptive. The data collection methods in this research are primary and secondary data. The analytical methods used are Chi Square analysis and Fishbein Multiattribute analysis. The results of the research show that all the attributes observed in this study, namely meat color, meat aroma, meat parts and cut shape, are significantly different within the 95% confidence level, meaning that there are differences in consumer preferences for the existing attributes (color, aroma, part and shape of the cut). on broiler chicken meat. Broiler chicken meat which is the consumer preference in traditional markets in Jember Regency is broiler chicken meat with attributes of choice including yellowish white color, non-fishy aroma, chicken thigh meat, and even cut shape. The attributes that are most considered and those that are least considered are color, aroma, part of the meat, shape of cut.

Extraction of the three-dimensional architecture of deformation bands from ground-penetrating radar cubes using multiattribute analysis

Fault zones in porous siliciclastic rocks can be dominated by deformation bands (DBs), which are small-scale tabular structures that usually occur as cluster features. DBs can reduce permeability, contributing to the compartmentalization of oil reservoirs and aquifers. DBs cannot be imaged by seismic methods, but can be imaged by Ground-penetrating radar (GPR). Although DBs and host rocks share the same lithology, GPR imaging is possible because DBs can cause small vertical offsets and reduce the amplitude of the GPR signals. We present an automatic approach for extracting the three-dimensional (3D) architecture of DBs from GPR cubes using multiattribute analysis. We used a 200 MHz GPR cube surveyed on an outcrop of a sandstone formation highly impacted by DBs in the Rio do Peixe Basin, northeastern Brazil. The multiattribute analysis is based on edge evidence and sequential ant-tracking, a combination that can identify narrow zones of attenuated GPR signals. Furthermore, the 3D architecture of DBs was extracted as a geobody using an opacity balancing operator. The geological reliability and limitations of the geobody were demonstrated by comparing slices of the geobody with images of exposed DBs in similar positions, in addition to structural measurements obtained in field and in the geobody.

Multi-Attribute Analysis for Sustainable Reclamation of Urban Industrial Sites: Case from Damascus Post-Conflict

Multi-Attribute Analysis for Sustainable Reclamation of Urban Industrial Sites: Case from Damascus Post-Conflict

Assessing environmental trade-offs in packaging systems for infant formula delivery: A cradle-to-gate plus end-of-life life cycle assessment

An LCA study was conducted comparing three packaging systems to deliver infant formula, including primary (plastic, composite, and steel containers), secondary (corrugated box), and tertiary (pallet) levels, all manufactured and distributed in North America. The project goal involved quantifying each system's environmental footprint (EF), evaluating the effect of end-of-life (EoL) modeling in LCA results, and interpreting trade-offs among environmental impact indicators.The functional unit was defined as a packaging system delivering 1000 g of infant formula from cradle-to-gate, plus EoL. The three packages, including EoL, were modeled using SimaPro 9.3.03, with TRACI 2.1 V1.06 Midpoint being the primary impact assessment method. The LCA was performed according to ISO 14040/14044 standards. EoL models included the cut-off method, the 50/50 allocation, and the circular footprint formula (CFF). The stochastic multi-attribute analysis (SMAA) method was implemented to evaluate the trade-offs among the midpoint indicators.The primary package significantly contributed to the three systems in all the evaluated categories. Adjusting the EoL models influences the overall results when comparing the packaging systems' impacts. Contributions in each category vary slightly, with minimal changeover from the highest or lowest package footprints in EoL models. The SMAA ranking preference for all EoL methods indicates that the plastic container is preferred, having the lowest EF with >50 % probability.Environmental impacts of the packages involved trade-off discussion. With the initial EoL methodology (cut-off method), Package 1 (plastic) shows the highest impact in 4 of the 10 impact categories, Package 2 (composite) in 2 of the 10 categories, and Package 3 (steel) in the remaining 4 categories. With the 50/50 allocation and CFF EoL methodologies, different conclusions were reached about the impacts of each package; however, SMAA results found that ranking of the packages within EoL methodologies did not change the conclusions that the plastic package is preferred.

Structural and seismic attribute analysis of the Paleocene carbonate reservoir from the Balkassar Field, Potwar Plateau, Pakistan

The structural and seismic properties of the Paleocene carbonate reservoir are re-evaluated, using 3D seismic data multi-attributes, to improve reservoir prediction accuracy rarely documented earlier. This study highlights a number of relevant post-stack seismic attributes for understanding the structural setup and seismic properties of a carbonate reservoir. The structural analysis was carried out using seismic interpretation, combined with multi-attribute analysis for prospect actualization and generation of a 3D structural model to determine the structural aspect. The structural interpretation reveals the presence of faults and an asymmetrical anticlinal structure demonstrating a four-way closure, confirming compressional tectonics. The high amplitude anomaly (-6 to 12) combined with the RMS attribute (23 to 32) suggests bright spots in the Paleocene carbonate reservoir and gas saturated zone, the variance attribute (0.05 to 0.03) highlights the presence of two major faults, and the lower instantaneous frequency demonstrates the presence of hydrocarbons. The attribute results indicate that the Lockhart Limestone possesses good reservoir potential as revealed by DHI (bright spot), gas saturated zone and a trapping mechanism supported by four-way structure closure in the region and can help to understand analogous carbonate reservoirs in similar geological settings around the world.

Application of a novel geometric seismic attribute for enhancing fault visualization in areas of potential carbon capture and storage

Seismic fault interpretation is a critical task for any type of energy industry. Correct fault mapping can be crucial for the success of a project. Common geometric seismic attributes, such as coherence and curvature, are routinely employed to enhance fault visualization in seismic data. However, they can show limitations for subseismic faulting. In this study, we highlight the usefulness of including novel aberrancy attributes for fault identification in multiattribute analysis and unsupervised machine learning (ML) techniques. We compare broadband coherence, curvature, multispectral coherence, and aberrancy when trying to map faults in a potential CO2 storage location. We also compare self-organizing maps and generative topographic mapping techniques when including and excluding aberrancy attributes. Our results show that integrating aberrancy attributes during multiattribute analysis and ML steps considerably enhanced the visualization of lineaments with strikes similar to those of fracture sets seen only with well-log data and that were not clearly captured by the conventional seismic attributes and ML scenarios excluding aberrancy attributes. We demonstrate the potential of these novel geometric seismic attributes to map subseismic faults. We also provide an example that can encourage interpreters to include them in their interpretation workflows.

Analisis Preferensi Konsumen Bunga Krisan Potong (Chrysanthemum morifolium) Di Jawa Timur

This study aims to analyze the attributes of cut chrysanthemums that have a relationship with the consumption of cut chrysanthemums in East Java, analyze the attributes of cut chrysanthemums that are preferred and most considered in East Java and analyze consumer attitudes towards the attributes of cut chrysanthemums in East Java. The research location was determined deliberately, namely in East Java which is a consumptive area for cut flowers. Respondents were determined by the Solvin Formula, namely 100 respondents. The analytical method used is the chi-square analysis method and fishbein multi-attribute analysis. The results showed that: Attributes that were significantly related to the consumption of cut chrysanthemum flowers were type attributes, consumer preferences in East Java were spray cut chrysanthemum flowers, white in color, and in the shape of a pompom. The attribute of cut chrysanthemums that is most considered in purchasing decisions is the color attribute. The most considered to the less considered attributes are color, shape, and type. Consumer attitudes towards the attributes of shape, type, and color of cut chrysanthemum flowers are positive.Keywords: Chrysanthemum Flower, Chi-Square Analysis, Consumer Preference, Fishbein Multiattribute Analysis

Analisis Selera Konsumen Terhadap Atribut Produk dalam Keputusan Pembelian Minuman Mixue

Mixue is an ice cream shop with cheap and delicious prices, making Mixue expand massively throughout Indonesia in a fairly short time. This study aims to identify and analyze the characteristics, purchasing decision process and consumer tastes towards the attributes of Mixue beverage products. This research was conducted at the Mixue shop in the Dharmawangsa and Ngagel Surabaya branches. The sampling technique was "accidental sampling" with a total of 84 consumers. The analytical method uses descriptive analysis and Fishbein multi-attribute analysis with the help of a questionnaire and Microsoft Excel 2019. Based on the analysis using Fishbein's multi-attributes, the attribute that has the most interest is price, while the attributes that consumers trust the most are price, brand. Based on the Fishbein score obtained at 101.69, it can be said that consumer tastes for Mixue beverage products are included in the like category.

Perilaku konsumen pada pembelian beras analog jagung di Kota Gorontalo

Introduction: Analog rice is a functional food made from part or all of non-rice ingredients consumed like eating rice in general. One of the analog rice that is widely consumed is corn rice. Consumption of corn rice has become a culture of the people of Gorontalo. The aims of this study were to (1) determine the attributes that influence the purchase decision of corn analog rice in Gorontalo City and (2) analyze consumer attitudes towards the attributes of corn analog rice in Gorontalo City. Method: The research was conducted at the Gorontalo City Central Market, with a total sample of 65 respondents who were selected by accidental sampling. Data analysis used descriptive analysis by making a frequency distribution table to determine the attributes that influence the purchase decision of corn analog rice in Gorontalo City. Multiattribute Fishbein analysis was used to analyze consumer attitudes towards the attributes of corn analog rice. Result: The results showed that the rice analogue of corn that respondents liked was rice with small/fine grain, yellow in color, aromatic, free from dregs, and cheap. After being cooked into rice has a sweet rice taste and fluffier texture. The results of the Fishbein Multi-attribute analysis showed that the quality of rice was ranked first with a score of 20,10 points, followed by the color of the rice with a score of 18,49 points. Conclusion: Attributes that influence the purchase decision of corn analog rice in Gorontalo City include the shape of rice grains, the taste of corn rice, the texture of corn rice, color, aroma, quality, and price of rice. Fishbein's multi-attribute analysis shows that the attributes of quality and color of corn rice are the most important considerations in purchasing corn analog rice.

CONSUMER ATTITUDE IN PURCHASING ORGANIC VEGETABLES IN SLEMAN REGENCY

Organic vegetables, increasingly popular in Sleman Regency, are chosen based on various attributes. This research investigates consumer attitudes toward these attributes and the characteristics of organic vegetable consumers in the area. Data were gathered from 50 respondents through interviews at organic farms, supermarkets, and organic product stores. The analysis used Fishbein multi-attribute analysis to assess consumer attitudes and cross-tabulation to identify consumer characteristics. Results indicated positive attitudes toward physical appearance and freshness, while attitudes toward price, variety, packaging, and organic labeling were neutral. The typical organic vegetable consumer in Sleman Regency is a married woman, aged 35-44, holding a bachelor's degree, employed as a housewife, with an average monthly family income exceeding Rp10,000,000.00.

Supervised machine learning for discriminating fluid saturation and presence in subsurface reservoirs

This paper describes a workflow that combines machine learning and frequency-related multi-attribute analyses to predict the occurrence of water, oil, and high or low gas saturations in three Miocene Gulf of Mexico clastic reservoirs, the Ursa, King Kong and Lisa Anne fields. The models are trained on labeled data from the Ursa Field dataset and validation is conducted on the King Kong and Lisa Anne Field datasets, comprising four wells with oil and varying gas saturations. We also analyze the impact of fluid-type and saturation on a suite of frequency-related attributes, including independent frequency magnitudes and spectral shape attributes.We also assess feature significance using SHAP Analysis and our results indicate that that high gas saturation is characterized by high magnitudes of low frequencies, increased bandwidth, and lower skewness and kurtosis values. Conversely, low gas saturation is distinguished by high magnitudes of medium frequencies, reduced bandwidth, and higher skewness and kurtosis values.Our workflow demonstrates the power and utility of supervised machine learning for reservoir fluid identification and saturation prediction. Human interpreters relying solely on post-stack seismic data may find the task of reservoir fluid predictions challenging and the results may be compromised by subjectivity. This study underscores the potential of machine learning to improve hydrocarbon exploration and production, providing a more robust approach to prospect risk assessment using post-stack seismic data and frequency attributes.

Multi-attribute analysis of adeno-associated virus by size exclusion chromatography with fluorescence and triple-wavelength UV detection

Adeno-associated virus (AAV) is the leading platform for in vivo gene therapy to treat numerous genetic diseases. Comprehensive analysis of the AAV particles is essential to ensure desired safety and efficacy. An array of techniques is required to evaluate their critical quality attributes. However, many of these techniques are expensive, time-consuming, labour-intensive, and varying in accuracy. Size exclusion chromatography coupled with fluorescence and triple-wavelength ultraviolet detection (SEC-FLD-TWUV) and incorporating an aromatic amino acid of tryptophan as an internal standard offers a simple, rapid, and reliable approach for simultaneous multi-attribute analysis of AAVs. In the current study, we demonstrate its capability for AAV characterization and quantification, that includes capsid concentration, empty to full capsid ratio, vector genome concentration, and the presence of aggregates or fragments. All were performed in 20-min chromatographic runs with minimal sample handling. Data analysis involves the assessment of intrinsic fluorescence and UV absorbance of samples at three wavelengths that can be utilised to determine the content of the capsid protein and genome copy number. The separation efficiency using SEC columns with different pore sizes, and elution buffers of varying compositions, ionic strength, and pH values was also evaluated. This SEC-FLD-TWUV method may serve as a powerful yet cost-effective tool for responsive quality evaluation of AAVs. This may enhance performance, robustness, and safety of bioprocessing for AAV vectors to be used in gene therapy.

Bipolar picture fuzzy hypersoft set-based performance analysis of abrasive textiles for enhanced quality control

Abrasive textiles have widespread industrial applications in the fields of polishing, finishing, deburring, and cleaning of various surfaces. Effective decision making and performance analysis are crucial in the development and manufacturing of abrasive textiles, as it enables manufacturers to evaluate and optimize the performance of these materials for specific applications and to make informed decisions about their production processes. For that purpose, this work aims to introduce an innovative bipolar picture fuzzy hypersoft set (BPFHSS) which is composed of two picture fuzzy hyper soft sets; one of them gives us the positive information, and the other gives us the negative information, for each membership degree, neutral membership, and non-membership degree. The properties of the designed structure and discussed alongside a thorough discussion on the De-Morgan's laws. Also, the bipolar picture fuzzy hypersoft weighted geometric (BPFHSWG) operator is defined for the BPFHSS framework to aggregate bipolar picture fuzzy hypersoft numbers (BPFHSN) information. This research highlights the importance of considering inconsistent, bipolar, and multiple sub-attribute information in decision-making processes by using the defined operators to develop an algorithm for a multi-attribute analysis for quality control of manufacture of abrasive textiles.

Analisis Preferensi Konsumen Terhadap Pembelian Dimsum Uma Yum Cha di Kota Surakarta

<p>AThe increase in public interest in consuming ready-made foods such as street food culinary and the number of street vendors in the food or beverage sector is quite high in Surakarta City making more diversity of consumer tastes in choosing snacks, one of the street foods is Uma Yum Cha dim sum. It is necessary to know about consumer preferences so that business owners are able to meet consumer expectations to provide satisfaction to consumers. This study aims to determine consumer preferences and what attributes are considered by consumers in purchasing Uma Yum Cha dim sum in Surakarta City. Sampling using purposive sampling method with 100 respondents. The analysis methods used are chi-square analysis and fishbein multiattribute analysis. The results showed that the categories of each attribute of Uma Yum Cha dim sum that became consumer preferences included dim sum with a slightly spicy savory taste, a quantity of 4 pcs, a soft texture, medium dim sum size, and promotion through internet media and the most considered attribute by consumers in purchasing Uma Yum Cha dim sum consecutively are taste, texture, quantity, size, and promotion</p>

Analysis Of Consumer Preferences In Buying Broiler Chicken Meat

In general, consumers in buying a product are closely related to the attributes attached to the product concerned. This is because these attributes will cause preference. Therefore, knowledge of attributes and preferences becomes very important, especially for manufacturers or traders. This study aims to: 1) find out the attributes of chicken meat that are consumer preferences and 2) find out the attributes that consumers consider most in buying broiler chicken meat. The research design used in this study was using quantitative descriptive methods with survey research methods. The population used is consumers who buy broiler chicken meat at the Pasar Minggu Traditional Market, Palimanan District, Cirebon Regency. The attributes studied in broiler chicken meat are the price of meat, meat parts, meat texture, and meat color. The number of samples used was 100 respondents with a sampling technique using accidental sampling. The study was conducted in July-August 2022. Data analysis techniques using chi square test and fishbein multiattribute analysis. The results showed that 1) there are differences in consumer preferences for the attributes that exist in broiler chicken meat. The attributes of broiler chicken meat that become consumer preferences are the price of meat, meat parts, meat texture, and meat color. The attributes of broiler chicken meat that consumers like are the price of meat IDR 30,000.-, the broiler chicken meat part is breast, the texture of broiler chicken meat is chewy texture, and the color of broiler chicken meat is yellowish white, 2) the attributes most considered by consumers in buying broiler chicken meat consecutively ranging from the highest to the lowest are the price of meat, meat color, texture of meat, and parts of meat

Analysis of Attitude and Consumer Preferences to Purchase Decisions of Banana Fruit in Traditional Markets Pangkalpinang City

This study examines consumer perceptions of the qualities considered in purchasing decisions and consumer preferences for purchasing bananas in traditional markets in Pangkalpinang. This research was carried out in a predetermined traditional market in Pangkalpinang City. This study used a survey method as its primary research design. Purposive sampling was used, and the sample size was 100 respondents. The attributes of bananas analyzed were tasted, fruit skin color, fruit size, and number of fruit per comb. The analytical method used is Fishbein Multiattribute analysis and Conjoint analysis. The results showed that consumer attitudes toward the attributes that were most considered in purchasing bananas were attributes of fruit skin color (21.57) which was very positive—taste (16.27), which was a positive value. Fruit size (15, 87) is a positive value, and the number of fruit per comb (6,41) is negative. Consumer preferences in purchasing bananas at the traditional Pangkalpinang City market are bananas with a yellow-green skin color, a sweet banana taste, a length of > 14 cm, and many pieces per comb with> 16 details. The sequence of importance values explains the attributes of bananas that the consumer pays the most attention to when buying bananas: the color of the banana peel, the taste of the banana, the size of the banana, and the number of bananas per comb.